Systems and methods for a home area recommender

ABSTRACT

Disclosed herein are a method, system, and computer-readable storage medium with instructions for recommending locations to a user. Preferred criteria may be selected by the user, for example, or a third party, and provide objective or subjective information that the user is seeking in a location. Embodiments may include compiling objective information with the location and comparing the objective information to preferred criteria. A user&#39;s profile may be compared to another person&#39;s profile, where the other person&#39;s profile is associated to the location. A location may be recommended to the user if the objective information correlates to the preferred criteria and if the other person&#39;s profile correlates to the user&#39;s profile. Subjective information associated with the location may be provided to the user along with the recommended location. Furthermore, a location may be recommended to the user if the subjective information correlates to the preferred criteria.

CROSS-REFERENCES TO RELATED APPLICATIONS

This application is a continuation of U.S. patent application Ser. No.12/059,474, filed Mar. 31, 2008, now U.S. Pat. No. 8,145,661, and isalso related by subject matter to the embodiments disclosed in thefollowing commonly assigned applications: U.S. patent application Ser.No. 12/059,351, filed Mar. 31, 2008; and U.S. patent application Ser.No. 12/059,563, filed Mar. 31, 2008, each entitled “SYSTEMS AND METHODSFOR A HOME AREA RECOMMENDER”. The disclosure of each application isincorporated by reference herein in its entirety.

BACKGROUND

Typically, individuals interested in purchasing or renting real estateoften desire to identify available properties that fall within thebounds of their selected search parameters (e.g., price range, squarefootage, number of bedrooms, etc.). The basic details about availableproperties are commonly available, such as through posted ads, a realestate agent, or a property listing service that maintains a database ofavailable properties.

Based on preferred criteria, an automated search may be performed by alisting service or agent, and a search report may be returned to theuser with available listings that satisfy the user's selected searchparameters. For example, the service or agent may send an email updateto an individual with information about select properties. The automaticsearch reports are convenient for a prospective buyer to be notified ofproperties that satisfy their search parameters. However, theinformation available to the user is limited, and the method ofproviding that information to the user is also limited.

The search parameters for searching properties are usually limited tobasic property details, such as a price range, a preferred number ofbedrooms and bathrooms, etc. Some listing services expand the searchoptions to include other common features of a property that users may beseeking. A user may have the option to select properties that have, forexample, a pool, or a finished basement, or a garage. Some servicesoffer access to additional information that is publicly available for aproperty location, such as neighborhood demographics, etc. Yet even withthis additional info, typically only basic details specific for aproperty are provided.

Many individuals consider other factors besides the basic details of anavailable property. Some individuals would like to know more broadlywhich neighborhoods or zip codes include features that appeal to theindividual, regardless of whether any available properties are within adesignated location. A real estate agent working for the buyer mayprovide more personalized information, such as details about the selleror information about the property that is shared between agents.However, the agent's knowledge is typically limited to the informationshared between agents or the agent's personal knowledge of the area.And, some prospective buyers do not want the hassle of dealing with anagent or do not fully trust the agent because the agent presumably hasthe motivation to make a commission.

Thus, a tool is desired that would allow individuals to obtain andbetter access property information beyond the basic details provided bylisting services, and to be able to share more reliable or trustedproperty- and neighborhood-related information. It would also bedesirable for a prospective buyer or renter to be automatically providedwith search results that are not limited to basic property information,but also include additional objective and subjective information aboutthe location.

SUMMARY

In view of the above shortcomings and drawbacks, computer-readablestorage media, methods, and computer systems for compiling basicproperty details and user-provided inputs to provide locationrecommendations to a user are provided.

A user's preferred search criteria, along with other data, may becompiled and compared to location-relevant information to make locationrecommendations. In an example embodiment, social networks provideaccess to location-relevant information. A social network system mayprovide a connection between people that facilitates interaction amongits users. In another example embodiment, a service provider returnssearches to a user based on member profiles and member inputs, locatingindividuals that are similarly situated. An aggregation of common realestate information combined with user-provided data may result in bettersearches for desired property.

This Summary is provided to introduce a selection of concepts in asimplified form that are further described below in the DetailedDescription. This Summary is not intended to identify key features oressential features of the claimed subject matter, nor is it intended tobe used as an aid in determining the scope of the claimed subjectmatter.

BRIEF DESCRIPTION OF THE DRAWINGS

FIG. 1 depicts an example configuration of a system that compileslocation-relevant information and recommends locations to a user.

FIG. 2 depicts an example method of recommending a location to a userbased on objective and subjective information.

FIG. 3 depicts an example method of recommending a location to a userbased on objective and user-relevant information.

FIG. 4 depicts an example configuration of a comparison module andscenario for recommending locations to a user.

FIG. 5 depicts an example configuration of entities that are networkedto perform the disclosed techniques.

FIG. 6 depicts an example method of a computing system that can performthe disclosed techniques.

DETAILED DESCRIPTION

Disclosed herein is an application for compiling location-relevant anduser-related information and using the compiled information to providelocation recommendations to a user. The subject matter of the disclosedembodiments is described with specificity to meet statutoryrequirements. However, the description itself is not intended to limitthe scope of this patent. Rather, the claimed subject matter might alsobe embodied in other ways, to include elements similar to the onesdescribed in this document in conjunction with other present or futuretechnologies.

FIG. 1 illustrates an example system 100 in which aspects of thetechniques described herein may be employed. System 100 may include auser 104 and a user profile 106, preferred criteria 110, and a device108 associated to the user 104. A user database 115 may be used to storeboth information about the user 104 and associated to the user 104.System 100 may include an objective information database 116, asubjective information database 120, and other person profiles 124 thatare associated to an associated location 122. The associated location122 may be defined narrowly, such as a single property location, or thelocation may be defined broadly and encompass, for example, aneighborhood, a region, an apartment complex, etc. Further, the systemmay include a social network 118, a service provider 114, and acomparison module 128. The components may communicate over acommunications network 102 to share information, as shown in FIG. 1. Anyof these components may have direct access to each other for sharing orstoring information.

System 100 can be used to recommend locations 126 to the user 104. Auser 104 may be, for example, a prospective buyer or renter of realestate, a realtor, or a business service. Preferred criteria 110 that isassociated to the user 104 may be set, and a user profile 106 associatedto the user 104 may be created. If the user is a realtor or a businessservice, the user profile 106 may be associated to a client. The user104 could use a device 108, such as a home computer, to input preferredcriteria 110 or create a user profile 106. The information could beshared over a communications network 102. The preferred criteria 110 andthe user profile 106 may be generated by an entity other than the user104, such as by a service provider 114. For example, if the user 104creates a profile 106 from his home computer, the user profile 106 maybe uploaded to a service provider 114, and the service provider 114 maygenerate preferred criteria 110 for the user 104 based on the userprofile 106. If the user 104 is a realtor, the realtor could upload auser profile 106 on behalf of a client. A user database 115 may becompiled that includes an identity of the user 104 linked to items inthe user profile 106, and/or preferred criteria 110 associated to theuser 104.

Each of the databases 115, 116, and 120, either separately or combined,may be provided as a database management system, an object-orienteddatabase management system, a relational database management system(e.g. DB2, Access, etc.), a file system or another conventional databasepackage. Further, the databases can be accessed via a Structure QueryLanguage (SQL) or other tools known to one of ordinary skill in the art.

A service provider 114 could be any entity that collects and storesinformation about a user 104. For example, the service provider 114could be a service that collects, stores, maintains, and provides realtyinformation, such as a listing service or agent agency. The serviceprovider 114 may be any organization or business that provides a serviceto a consumer or business, or the like. Examples of such entitiesinclude membership organizations, such as employer/employeeorganizations, and providers of services, such as insurance companies,home-locator services, employers seeking to provide information to itsemployees, or the like.

The service provider 114 may generate profiles based on informationprovided by its customers, or collect the information from profilescreated remotely. For example, if the service provider 114 is aninsurance agency, the agency may collect and store information about itspolicy-holders. The service provider 114 may maintain the user profile106 or have access to user profiles 106 over a communications network102.

An objective information database 116 may compile objective informationassociated to an associated location 122. The objective information mayinclude information from any source that can provide objectiveinformation about a location such as an associated location 122. Forexample, a service provider 114 such as a listing service could providerealty details to the objective information database 116 for storage.Often, realty listing services have access to the commonly known“multiple listing service” (MLS), which is a group of private realtydatabases used by real estate brokers representing sellers to shareinformation about properties with other real estate brokers. Local andprivate databases may also be maintained by associations of realtors,such as real estate agencies, that each has a reciprocal accessagreement with the MLS. Other public and private listing servicesmaintain property information. For example, for-sale-by-owner listingservices enable a seller acting as a for-sale-by-owner, who cannot put alisting directly on the MLS, to list his properties so that they aresearchable by prospective buyers. Any of these services could provideobjective information to the objective information database 116 that isassociated with a location.

A listing service such as those described typically provides basic realestate information specific to realty that is for sale or rent. Thesedetails may be data about the property, such as the number of bedrooms,price range, or if there is a pool, for example. Where the associatedlocation 122 is a single realty location, the objective informationdatabase 116 may also compile information specific to the property, suchas realty sale history, zoning parameters, or an estimated home value,for example. The objective information database 116 may also beassociated to an associated location 122 that is not a single realty.For example, the associated location 122 could be defined by a zip code.The objective information database 116 may compile information about thezip code, which may include basic real estate details about properties,for sale or not, within that zip code. The objective informationdatabase 116 may also include other objective details associated to theassociated location 122, such as neighborhood demographics, grocerystore locations, realty information, any available realty locations,neighborhood demographics, realty sale history, etc.

Many individuals consider other factors besides objective information,such as subjective information, to determine if a location appeals tothem. Subjective information may be information belonging to a subjectrather than to the object of thought, such as an individual's opinionsabout a location. For example, prospective buyers of real estate in anarea may be interested in knowing a resident's opinion and assessment oflocation-relevant attributes, such as how busy they think traffic is inthe area or if a neighbor has an incessantly barking dog. Prospectiverenters may want opinions from current or previous tenants, such astheir opinion about whether an apartment building is “kid-friendly,” orif their landlord has a tendency to delay fixing reported problems. Asubjective information database 120 may compile the subjectiveinformation associated to the associated location 122.

In an example embodiment, system 100 may include a social network 118for collecting information associated to an associated location 122,including subjective information that is compiled by the subjectiveinformation database 120. Social networking services are becoming morecommonplace for building online social relationships for communities ofpeople that share interests and activities. The social network 118 maybe web-based and provide a variety of ways for users 104 and tointeract, such as through chat programs, email, video, file sharing,discussion groups, etc. The social networks 118 may have additionalfeatures, such as the ability to create groups that share commoninterests or affiliations, upload videos, or hold discussions in forums.The user 104 may input a user profile 106 onto the social network 118.Other users may also create profiles on the social network 118, inputcomments onto the social network 118, or access information from thesocial network 118.

In general, social networking services break down into two broadcategories: internal social networking (ISN) and external socialnetworking (ESN) sites. An ISN is a closed/private community thatconsists of a group of people within a company, association, society,education provider and organization or even an “invite only” groupcreated by a user 104 in an ESN. An ESN is open/public and available toall web users to communicate and are designed to attract advertisers.

Services such as social networking sites, and the like, typicallycontain directories of some categories, such as former classmates,connecting with friends, etc. Personal networks may be created betweenfriends, family, colleagues, classmates, or people who are otherwisesimilarly situated. Individuals tend to be more likely to trust andvalue the opinions of people they know, and the network relationshipsprovide a way for people to connect to more people. Individuals willalso be more likely to trust people who are similarly situated, even ifthey do not know them personally. For example, employees of the samecompany who are located in different parts of the country or world maytrust or value the opinion of a fellow employee who they have never metin person merely because they have similar circumstance.

Thus, the subjective information database 120 may compile informationthat is stored, input, or otherwise gathered through the social network118, and this subjective information may be associated to an associatedlocation 122. For example, a contributor to the social network 118 couldinclude a comment about a certain location or provide information abouta particular neighborhood by tagging the comment with the correspondinglocation. The information may be specific to an address or be broadinformation about an area. For example, a user 104 of the social network118 could identify an address and include a note about a very noisy dog.Or, a user 104 could select an area by zip code or neighborhood name andprovide an opinion about traffic or speculations as to why a road isclosed to the public, for example.

The subjective information database 120 may compile information from asocial network 118 or any other source that may provide subjectiveinformation. Any entity that gathers or stores subjective informationmay compile the subjective information or manage the subjectiveinformation database 120. For example, if the service provider 114 is anemployer who regularly seeks suitable locations for relocatingemployees, the employer may gather subjective information associated tovarious locations from employees and store it in the subjectiveinformation database 120. Another example of a service provider 114 is ahome locator service that obtains subjective information from clients ona regular basis and may provide that information for compilation in thesubjective information database 120.

User profiles 106 and other person profiles 124 may include informationfrom a variety of sources. For example, the profiles 106 and 124 couldbe created on the social network 118 or uploaded from a service provider114 or stored by an employer. For example, an employer may have adatabase of employee 104 information that includes the user profile 106or other person profile 124. The service provider 114 could be anorganization, such as an insurance provider, that maintains customerinformation. A realtor may input a user profile 106 on behalf of aclient.

The other person profiles 124 are associated with a location, such asassociated location 122, so the information in the other person profile124 may also be associated to the associated location 122. For example,another person profile 124 may include an individual's name, age, andprofession, and be associated to the person's residential address. Thus,an individual may provide information about a location on a socialnetwork 118, for example, and the profile 124 could be associated to oneassociated location, such as associated location 122. However, theinformation that the individual places on the social network 118 couldbe associated with a different location, the different location beingthe location for which the individual is providing information. Forexample, the individual could select an address or a street and providesubjective information, despite where the user resides. As describedabove, the subjective information database 120 may compile and link boththe information and the associated location 122.

Thus, a collaboration of the components in system 100 could result inthe aggregation of location-relevant and people-relevant information. Acomparison module 128 may then use this information to provide arecommended location 126 to the user. The entity that uses thecomparison module 128 may automatically generate and provide therecommended location(s) 126 to a user. Thus, the user 104 does not haveto search through a social network 118 to find out certain information.For example, the user 104 could receive daily email updates with therecommendations.

FIG. 2 depicts an example method for recommending locations to a user104 based on objective and subjective information associated to thelocations. At 202, a database may compile objective informationassociated to various locations. The objective information may bespecific, such as information about a particular property, or bebroader, such as information about a zip code or a neighborhood. Theobjective information may include specific details about a property orproperties within the location, an indication if any properties are forsale or rent, local attractions, information regarding sex offenders,zoning issues, etc. The objective information may include publiclyavailable information, such as neighborhood demographics, area history,history of home sales in the location, etc.

An entity, such as a user or a third party, may select preferredcriteria for the user 104 at 204. The preferred criteria 110 may providebaseline search parameters associated to the user 104. For example, theuser 104 may be looking to purchase realty, and may set preferredcriteria to include search parameters of a desired property. The searchparameters could be objective information desired in a specificproperty, such as the number of bedrooms, price range, and squarefootage, for example. The preferred criteria 110 may also includeinformation that can be measured subjectively.

The user's preferred criteria 110 may be set by the user 104 or by athird party. A third party may use items in a user's profile or othercharacteristics of the user to generate preferred criteria 110associated with the user. Typically the third party has some informationabout the user. For example, a home locator service could obtaininformation about the user 104 and set preferred criteria 110 based onthe user 104 and/or a user's profile 106. In another example, the user'sfinancial advisor could set a price range in the preferred criteria 110based on the user's financial outlook, for example.

At 206, a database may compile subjective information associated tovarious locations. For example, a member of a social network 118 couldinclude a comment about a certain location in a blog on the socialnetwork, or provide information about a neighborhood in a chat room. Theinformation may be specific to an address or be broad information aboutan area. For example, a user 104 of the social network 118 couldidentify an address and include a note about a very noisy dog. Or, auser 104 could select an area by zip code or neighborhood name andprovide an opinion about traffic or recommend restaurants, for example.Social network users may select neighborhoods to chat about, orsubscribe to areas based on where they live to participate in discussiongroups, etc. The social network 118 may compile the subjectiveinformation from its users.

Further, any source with access to subjective information associatedwith a location may compile the information. For example, an employermay gather subjective information associated with a location from itsemployees. Another example is a home locator service that receivessubjective information associated to various locations from theirclients on a regular basis.

At 208 and 210, an entity such as a comparison module may compare theobjective information and subjective information, respectively, to thepreferred criteria set at 204. At 208, the determination is made whetherany of the objective information correlates to the preferred criteria110. At 210, the determination is made whether any of the subjectiveinformation correlates to the preferred criteria 110.

Information correlates to the preferred criteria if there is at leastone matching item or similar concept. For example, objective informationabout a specific property location that has three bedrooms and threebathrooms correlates positively to preferred criteria that is set tothree bedrooms and three bathrooms. In another example, the preferredcriteria may be set for locations with low traffic. The subjectiveinformation could be based on user-inputs or opinions about traffic, andthe objective information may be based on information provided by alocal department of transportation, for example.

Both subjective and objective information may correlate to preferredcriteria, such as preferred criteria set for a location with lowtraffic. The preferred criteria may have a high correlation to thesubjective information, for example, if the compilation of subjectiveinformation highly suggests low traffic in the location. The correlationmay be low, as well, such as if mixed opinions about traffic areprovided. Providing the recommended locations to the user may includeranking the locations based on the level of correlation. Locations mayalso be eliminated as a potential recommended location 126 if there is ano correlation between the preferred criteria and either the subjectiveor objective information.

If both the objective information and the subjective information docorrelate to the preferred criteria at 208 and 210, then an entity maycompare the respective locations associated to the objective informationand subjective information at 212. If any of those locations are a matchat 214, then the entity may recommend the location to a user at 216. Inanother embodiment, the resulting matching locations at 214 may beprovided at 218 for an input into another comparison, which will bedescribed with respect to FIG. 3 below.

The compared locations may be a match if there is an exact propertyaddress. The locations may also be a match if they are in proximity toeach other, such as within a certain range from each other or in thesame zip code, for example. The location returned to the user 104 may bebroader in this sense, such as being defined by the zip code. Thepreferences regarding the type of information received may be set by theuser 104 in this regard.

At 216, the entity recommending the locations may automatically generatea report and provide the report that includes the recommendedlocation(s) to the user 104. As described above, the user 104 may selectsubjective information in the preferred criteria 110, such that alocation will not be recommended if the subjective informationassociated with the location does not correlate with his preferredcriteria 110. Once a recommended location is determined, however, theuser 104 may desire any or all of the available subjective informationassociated with the recommended location, at 218.

Thus, at 218, the user may receive subjective information that isassociated with the recommended location without regard to whether theinformation correlated to the preferred criteria at 210. For example,the user 104 may wish to receive a report of recommended locations andadditionally receive any available subjective information available forthat location. The user 104 may also specify the type of subjectiveinformation to be included with the recommended locations at 218. Forexample, the user's preferred criteria 110 may include a request toreceive only particular topics of subjective information about therecommended locations 126, such as opinions of other users regarding thetraffic or safety.

FIG. 3 depicts an example method for recommending locations to a user104 based on information in a user's profile 106 and objectiveinformation associated with a location. This method enables a user 104to not only identify properties that are within their preferredcriteria, but also locations that are in proximity to individuals withcharacteristics that are similar to the user.

The user profile generated at 302 may include information about theuser, such as the user's age, profession, employer, or marital status,for example. Other person profiles 124 may include similar objectivedetails about other individuals. The user or a third party may createthe user profile 302. A service provider or organization may store theprofiles. For example, a user's insurance company or bank may storedetails about the user 104 that could make up the user's profile. Onlinedatabases may maintain profile information pertaining to a member aswell, such as social networking websites.

A database may compile objective information associated with locationsat 304. A comparison module may compare the objective information to auser's preferred criteria at 310 to determine if any of the objectiveinformation correlates to the preferred criteria. At 312, a comparisonmodule may compare the user's profile 106 to the other person's profile124 to find other individuals who share characteristics with the user104. An item in the user profile to be compared with items in otherperson profiles 124 may be specifically selected as a comparison item.Profiles correlate if they share at least one matching item or similarconcept. Locations may also be eliminated as a potential recommendedlocation 126 if there is a negative correlation between the user profile106 and another person profile 124.

If the objective information correlates to the preferred criteria at310, and an item in the user's profile 106 correlates to an item inanother person's profile at 312, then the comparison module may comparethe respective locations associated with the compiled objectiveinformation and the other person's profile. The compared locations maybe a match if there is an exact property address. The locations may alsobe a match if they are in proximity to each other, such as within acertain range from each other or in the same zip code, for example. Thelocation returned to the user 104 may be broader in this sense, such asbeing defined by the zip code. The preferences regarding the type ofinformation received may be set by the user 104 in this regard.

If any of those locations are a match at 316, then the location isrecommended to a user 104 at 318. An entity may automatically generate areport with the recommended locations and provide the report to the user104 providing the recommended location. Furthermore, at 320, an entitymay provide subjective information that is associated with therecommended location 126 to the user. The subjective information may beprovided regardless of whether the information correlated to thepreferred criteria 110. For example, the user 104 may wish to receive areport of recommended locations and additionally receive any availablesubjective information available for that location. The user 104 mayalso specify the type of subjective information to be included with therecommended locations at 218.

In another embodiment, the comparison module may compare the resultingmatching locations at 316 to the matching location at 322. Thus, at 322,the comparison module may compare locations that are associated withobjective information, locations associated with subjective information,and locations associated with other similarly situated individuals.

As described herein with respect to the comparisons of location-relevantinformation, the recommended locations may result from comparisons ofany combination of the location-relevant information thereof. Forexample, a user 104 may desire to receive the locations that correlateobjectively and subjectively to his preferred criteria, but not care ifhe is located near individuals with anything in common with him. Thus,the automatically generated report could include the recommendedlocations as described in FIG. 2 at 216. These recommended locations arethe overlapping locations that are based on compiled objectiveinformation and compiled subjective information.

Similarly, the user 104 may select to receive the locations that overlapbased on the sources of information, thus receiving the automatic searchresults as described in FIG. 3 at 324. Thus, the combination ofoverlapping search results can provide for a more focused search basedon a user's preferred criteria. The overlapping locations recommended tothe user 104 may be exact property matches, for example, or they couldbe regions, such as a zip code, that represents the overlappinglocations.

FIG. 4 depicts a graphical representation of the comparison module 128and the inputs to the comparison module 128 with respect to an exemplaryuser 104. The comparison module 128 may compare information from theuser database 115, an objective information database 116, a subjectiveinformation database 120, and other person profiles 124. As describedherein, the objective information database 116 and the subjectiveinformation database 120 may compile information associated with alocation from a variety of sources, and the other person profiles 124may be generated in a variety of ways.

The user database 115 may include a USERID 404 that corresponds to auser profile 106 and preferred criteria 110 that is associated with auser. The user profile 106 may include information about the user. Theinformation may be objective details, such as the user's age,profession, employer, or marital status, for example. The example userprofile 106 depicted in FIG. 4 represents the profile of an active dutyofficer in the military, as indicated by his user profile 106. The userprofile 106 includes the user's 104 name, Jason Lee, and age, 34, etc.as an example of the information include in a user profile. The userprofile 106 may include any descriptive or objective details about theuser 104.

The example preferred criteria 110 indicates, in part, that the user 104is seeking property locations that have three bedrooms, two baths, andare within three miles of a golf course. The comparison module 128 maysearch the objective information database 116 and compare the preferredcriteria 110 associated with the user 104 to the objective informationcompiled in the objective information database 116. If any informationcompared correlates, the locations associated with the objectiveinformation may be a first set of recommended results. In this example,an example recommended location is recommended location 126. Thelocation summary 426 for the recommended location indicates the locationas Spring Lane Meadows. Spring Lane Meadows is a neighborhood that hasat least one property with three bedrooms and two baths within threemiles of a golf course. The location summary 426 gives an example ofwhat the compiled objective information for a recommended location 126may include.

The user 104 may wish to live near other people who are similar to theuser 104. The comparison module 128 may identify locations withobjective information that correlates to the user's preferred criteria110, but are also in proximity to other individuals that have similarcharacteristics to the user 104. For example, the comparison module 128may compare other person profiles 124 to the user profile 106 bycomparing an item in the user profile 106 to items in other personprofiles 124. A particular item may be selected as a comparison item. Ifan item in the user profile 106, or a select comparison item chosen bythe user, correlates to items in any of the other person profiles 124,the locations associated with the other person profiles 124 may be asecond set of results. If any of the first set of results includes alocation that is the same as a location in the second set of results,the location may be recommended to the user.

For example, assume the user 104 has to relocate and would like to liveclose to other active duty military personnel with a similar ranking.The user 104 selects those items from the profile as selected items 420to search for in the other person profiles 124. In this example, theuser 104 has therefore selected his profession and rank to be searchcriteria for in other person profiles 124. For example, person #1 may bean active duty military with an E-6 ranking associated with a propertyin the neighborhood Spring Lane Meadows. Thus, because Spring LaneMeadows is a location that correlates to the user's preferred criteria110 and is the same as the neighborhood that person #I lives in, theneighborhood is recommended to the user 104 in an automaticallygenerated search report.

The preferred criteria 110 may also include information that could bemeasured subjectively. The comparison module 128 may produce a third setof results by comparing the preferred criteria 110 to the subjectiveinformation in the subjective information database 120. The user 104could narrow the search by setting subjective information in thepreferred criteria 110. For example, the user's preferred criteria 110is set for quiet neighborhoods. If any subjective information associatedwith a location correlates to the user's preferred criterion, then thoselocations may either be a part of a third set of results if there is apositive correlation to the user's subjective criteria, or eliminated asa recommended location 126 if there is a negative correlation to theuser's subjective criteria.

FIG. 4 illustrates the use of a social network 118 to gather subjectiveinformation about a location. With respect to location 102, Person #1and Person #2 are exemplary users of a social network 118, each havinganother person profile, other person profile #1 and #2, on the socialnetwork 118. Person #1 is associated with the Spring Lane Meadowslocation because he lives on one of the streets. Person #2 is associatedwith the Spring Lane Meadows location because he provided information onthe social network 118 with respect to Spring Lane Meadows, by choosingthe location and providing data. If a user provides information for alocation for which he does not reside, an indication may be includedwith the information provided. Social network users can contribute datathrough a blog 411, chat 417, email 412, video 414, file sharing 413,etc. The user on the social network could select a location, such asSpring Lane Meadows 418, from a pull-down menu, by doing a search, etc.,and can input information about the location. If a search of thesubjective information on the social network 118 that is associated withSpring Lane Meadows indicates that the location represents a quietneighborhood, then the location may be recommended to the user.

The comparison module 128 may recommend locations based on locations ineach set of results in any combination. For example, a user 104 maydesire objective and subjective information that correlates to preferredcriteria 110, but not care the location is near individuals with atleast one common profile item. Thus, the recommended locations would beoverlapping locations in the first and second sets of results.Similarly, the user 104 could request those locations that overlap allthree sets. Thus, the combination of overlapping search results canprovide for a more focused search based on a user's preferences.Overlapping locations may be exact property matches, for example, orthey could be overlapping regions that surround each location.

Furthermore, a user may request to receive subjective information in thesubjective information database 120 that is associated with therecommended location 126 in addition to the recommended locations (i.e.,not input into the comparison module 128). For example, the user 104 maywish to receive subjective information as a compilation of anysubjective information associated with the location. The comparisonmodule 128 may recommend the neighborhood Spring Lane Meadows to a user104 based on overlapping locations from any combination of the first,second, and third search sets. Included with the search results may be acompilation of any subjective information from the subjectiveinformation database 120 that is associated with Spring Lane Meadows.

The user 104 may select to receive subjective information from similarlysituated individuals. For example, a location may be recommended to theuser where another person's profile that correlates to the user'sprofile is associated with the location. The user may also receivesubjective information from that same correlating other person'sprofile, or alternatively, receive subjective information associatedwith a different other person's profile that correlates to the user'sprofile.

The user 104 may limit the information received by selecting to receivethe subjective information only from similarly situated individuals.Thus, the comparison module 128 may compare the other person profile 124for the individual that contributed the subjective information. If theother person profile 124 correlates to the user profile 106, then thesubjective information provided by that individual may be included forthe user. For example, the user 104 may choose to receive subjectiveinformation from individuals with the selected item in their otherperson profile 124. The user 104 in this example can therefore limit theinformation received to be opinions about the recommended location 126from other active duty military personnel that are similarly situated.Individuals may be more likely to trust and value the opinions of peoplethey know or share similar features with, and the techniques describedherein provide a way for people to obtain that information. Thesubjective information associated with another person's profile may bereceived.

FIG. 5 depicts several entities that are configured in an exemplarynetworked computing environment, each implementing computerizedprocesses to perform the applications described above. One of ordinaryskill in the art can appreciate that networks can connect any computeror other client or server device. In this regard, any computer system orenvironment having any number of processing, memory, or storage units,and any number of applications and processes occurring simultaneously isconsidered suitable for use in connection with the systems and methodsprovided.

FIG. 5 provides a schematic diagram of an exemplary networked computingenvironment with different entities networked to provide a user withrecommended location 126s using the techniques disclosed herein. Theexemplary entities that may collaborate to perform the techniques are afinancial institution, a home locator service, and a social networkadministrator. The user may use computing device 552 to obtain theautomatically generated results from the home locator service. Theenvironment comprises computing devices 552, 554, 556, and 558 that areassociated with each of entities, 502, 504, 506, and 508. Each computingdevice 554, 556, and 558 may be associated with a database, such as auser database 514, an objective information database 516, and asubjective information database 518, respectively.

In the example configuration described in FIG. 5, the user may requestthat a home locator service provide recommended locations. The homelocator service may request and receive user information from the user'sfinancial institution, such as their financial means, descriptiveinformation about the user, etc. The home locator may select preferredcriteria 110 based on the user data retrieved from the financialinstitution. The home locator service may run a search on locations thatsatisfy the preferred criteria 110 set for the user. Based on theresulting locations, the home locator service may request subjectiveinformation pertaining to those locations. The home locator service mayeliminate locations from the search based on the subjective information.The home locator service may return the recommended location 126s to theuser.

Each of these computing devices 552, 554, 556, and 558 may comprise ormake use of programs, methods, data stores, programmable logic, etc. Thecomputing devices 552, 554, 556, and 558 may span portions of the sameor different devices such as PDAs, audio/video devices, MP3 players,personal computers, etc. Each entity 502, 504, 506, and 508 cancommunicate with another entity 502, 504, 506, and 508 by way of thecommunications network 570. In this regard, any entity may beresponsible for the maintenance and updating of a database 514, 516, 518or other storage element.

This network 570 may itself comprise other computing entities thatprovide services to the system of FIG. 5, and may itself representmultiple interconnected networks. In accordance with an aspect of thepresently disclosed subject matter, each device 552, 554, 556, and 558may contain discrete functional program modules that might make use ofan API, or other object, software, firmware and/or hardware, to requestservices of or information from one or more of the other entities 552,554, 556, and 558. For example, the home locator service 506 can requestsubjective information from the social network administrator over thecommunications network. The social network administrator may search thesubjective information database and send a packet of data through thecomputing device 558 over the communications network 570. The computingdevice 556 associated with the home locator service may then receive thepacket of information.

It can also be appreciated that any computing device, 552, 554, 556, or558, may be another type of device or be hosted on another computingdevice 552. Thus, although the physical environment depicted may showthe connected devices as computers, such illustration is merelyexemplary and the physical environment may alternatively be depicted ordescribed comprising various digital devices such as PDAs, televisions,MP3 players, etc., software objects such as interfaces, COM objects andthe like.

There are a variety of systems, components, and network configurationsthat support networked computing environments. For example, computingsystems may be connected together by wired or wireless systems, by localnetworks or widely distributed networks. Currently, many networks arecoupled to the Internet, which provides an infrastructure for widelydistributed computing and encompasses many different networks. Any suchinfrastructures, whether coupled to the Internet or not, may be used inconjunction with the systems and methods provided.

A network infrastructure may enable a host of network topologies such asclient/server, peer-to-peer, or hybrid architectures. The “client” is amember of a class or group that uses the services of another class orgroup to which it is not related. In computing, a client is a process,i.e., roughly a set of instructions or tasks, that requests a serviceprovided by another program. The client process uses the requestedservice without having to “know” any working details about the otherprogram or the service itself. In a client/server architecture,particularly a networked system, a client is usually a computer thataccesses shared network resources provided by another computer, e.g., aserver. In the example of FIG. 6, any device 552, 554, 556, 558 can beconsidered a client, a server, or both, depending on the circumstances.

A server is typically, though not necessarily, a remote computer systemaccessible over a remote or local network, such as the Internet. Theclient process may be active in a first computer system, and the serverprocess may be active in a second computer system, communicating withone another over a communications medium, thus providing distributedfunctionality and allowing multiple clients to take advantage of theinformation-gathering capabilities of the server. Any software objectsmay be distributed across multiple computing devices or objects.

Client(s) and server(s) communicate with one another using thefunctionality provided by protocol layer(s). For example, HyperTextTransfer Protocol (HTTP) is a common protocol that is used inconjunction with the World Wide Web (WWW), or “the Web.” Typically, acomputer network address such as an Internet Protocol (IP) address orother reference such as a Universal Resource Locator (URL) can be usedto identify the server or client computers to each other. The networkaddress can be referred to as a URL address. Communication can beprovided over a communications medium, e.g, client(s) and server(s) maybe coupled to one another via TCP/IP connection(s) for high-capacitycommunication.

FIG. 6 depicts a block diagram representing an exemplary computingdevice suitable for use in conjunction with implementing the systems andmethods described above. The computing device may be used by a user forreceiving recommend locations. An entity that compiles information andcompares the information against a user's preferred criteria 110 maysimilarly use a device such as that depicted in FIG. 6. For example, thecomputer executable instructions that carry out the processes andmethods described herein may reside and/or be executed in such acomputing environment as shown in FIG. 5. The computing systemenvironment 620 is only one example of a suitable computing environmentand is not intended to suggest any limitation as to the scope of use orfunctionality of the presently disclosed subject matter. Neither shouldthe computing environment 620 be interpreted as having any dependency orrequirement relating to any one or combination of components illustratedin the exemplary operating environment 620.

Aspects of the presently disclosed subject matter are operational withnumerous other general purpose or special purpose computing systemenvironments or configurations. Examples of well-known computingsystems, environments, and/or configurations that may be suitable foruse with the this subject matter include, but are not limited to,personal computers, server computers, hand-held or laptop devices,multiprocessor systems, microprocessor-based systems, set top boxes,programmable consumer electronics, network PCs, minicomputers, mainframecomputers, distributed computing environments that include any of theabove systems or devices, and the like.

Aspects of the presently disclosed subject matter may be implemented inthe general context of computer-executable instructions, such as programmodules, being executed by a computer. Generally, program modulesinclude routines, programs, objects, components, data structures, etc.that performs particular tasks or implement particular abstract datatypes. Aspects of the presently disclosed subject matter may also bepracticed in distributed computing environments where tasks areperformed by remote processing devices that are linked through acommunications network. In a distributed computing environment, programmodules may be located in both local and remote computer storage mediaincluding memory storage devices.

An exemplary system for implementing aspects of the presently disclosedsubject matter includes a general purpose computing device in the formof a computer 641. Components of computer 641 may include, but are notlimited to, a processing unit 659, a system memory 622, and a system bus621 that couples various system components including the system memoryto the processing unit 659. The system bus 621 may be any of severaltypes of bus structures including a memory bus or memory controller, aperipheral bus, and a local bus using any of a variety of busarchitectures. By way of example, and not limitation, such architecturesinclude Industry Standard Architecture (ISA) bus, Micro ChannelArchitecture (MCA) bus, Enhanced ISA (EISA) bus, Video ElectronicsStandards Association (VESA) local bus, and Peripheral ComponentInterconnect (PCI) bus also known as Mezzanine bus.

Computer 641 typically includes a variety of computer readable media.Computer readable media can be any available media that can be accessedby computer 641 and includes both volatile and nonvolatile media,removable and non-removable media. By way of example, and notlimitation, computer readable media may comprise computer storage mediaand communication media. Computer storage media include both volatileand nonvolatile, removable and non-removable media implemented in anymethod or technology for storage of information such as computerreadable instructions, data structures, program modules or other data.Computer storage media include, but are not limited to, RAM, ROM,EEPROM, flash memory or other memory technology, CD-ROM, digitalversatile disks (DVD) or other optical disk storage, magnetic cassettes,magnetic tape, magnetic disk storage or other magnetic storage devices,or any other medium which can be used to store the desired informationand which can accessed by computer 641. Communication media typicallyembody computer readable instructions, data structures, program modulesor other data in a modulated data signal such as a carrier wave or othertransport mechanism and include any information delivery media. The term“modulated data signal” means a signal that has one or more of itscharacteristics set or changed in such a manner as to encode informationin the signal. By way of example, and not limitation, communicationmedia includes wired media such as a wired network or direct-wiredconnection, and wireless media such as acoustic, radio-frequency (RF),infrared and other wireless media. Combinations of the any of the aboveshould also be included within the scope of computer readable media.

The system memory 622 includes computer storage media in the form ofvolatile and/or nonvolatile memory such as read only memory (ROM) 623and random access memory (RAM) 660. A basic input/output system 624(BIOS), containing the basic routines that help to transfer informationbetween elements within computer 641, such as during start-up, istypically stored in ROM 623. RAM 660 typically contains data and/orprogram modules that are immediately accessible to and/or presentlybeing operated on by processing unit 659. By way of example, and notlimitation, FIG. 6 illustrates operating system 625, applicationprograms 626, other program modules 627, and program data 628.

The computer 641 may also include other removable/non-removable,volatile/nonvolatile computer storage media. By way of example only,FIG. 6 illustrates a hard disk drive 638 that reads from or writes tonon-removable, nonvolatile magnetic media, a magnetic disk drive 639that reads from or writes to a removable, nonvolatile magnetic disk 254,and an optical disk drive 640 that reads from or writes to a removable,nonvolatile optical disk 653 such as a CD ROM or other optical media.Other removable/non-removable, volatile/nonvolatile computer storagemedia that can be used in the exemplary operating environment include,but are not limited to, magnetic tape cassettes, flash memory cards,digital versatile disks, digital video tape, solid state RAM, solidstate ROM, and the like. The hard disk drive 638 is typically connectedto the system bus 621 through an non-removable memory interface such asinterface 634, and magnetic disk drive 639 and optical disk drive 640are typically connected to the system bus 621 by a removable memoryinterface, such as interface 635.

The drives and their associated computer storage media discussed aboveand illustrated in FIG. 6, provide storage of computer readableinstructions, data structures, program modules and other data for thecomputer 641. In FIG. 6, for example, hard disk drive 638 is illustratedas storing operating system 658, application programs 657, other programmodules 656, and program data 655. Note that these components can eitherbe the same as or different from operating system 625, applicationprograms 626, other program modules 627, and program data 628. Operatingsystem 658, application programs 657, other program modules 656, andprogram data 655 are given different numbers here to illustrate that, ata minimum, they are different copies. A user may enter commands andinformation into the computer 641 through input devices such as akeyboard 651 and pointing device 652, commonly referred to as a mouse,trackball, or touch pad. Other input devices (not shown) may include amicrophone, joystick, game pad, satellite dish, scanner, or the like.These and other input devices are often connected to the processing unit659 through a user input interface 636 that is coupled to the systembus, but may be connected by other interface and bus structures, such asa parallel port, game port or a universal serial bus (USB). A monitor642 or other type of display device is also connected to the system bus621 via an interface, such as a video interface 632. In addition to themonitor, computers may also include other peripheral output devices suchas speakers 644 and printer 643, which may be connected through anoutput peripheral interface 633.

The computer 641 may operate in a networked environment using logicalconnections to one or more remote computers, such as a remote computer646. The remote computer 646 may be a personal computer, a server, arouter, a network PC, a peer device or other common network node, andtypically includes many or all of the elements described above relativeto the computer 641, although only a memory storage device 647 as beenillustrated in FIG. 6. The logical connections depicted in FIG. 6include a local area network (LAN) 645 and a wide area network (WAN)649, but may also include other networks. Such networking environmentsare commonplace in offices, enterprise-wide computer networks,intranets, and the Internet.

When used in a LAN networking environment, the computer 641 is connectedto the LAN 645 through a network interface or adapter 637. When used ina WAN networking environment, the computer 641 typically includes amodem 650 or other means for establishing communications over the WAN649, such as the Internet. The modem 650, which may be internal orexternal, may be connected to the system bus 621 via the user inputinterface 636, or other appropriate mechanism. In a networkedenvironment, program modules depicted relative to the computer 641, orportions thereof, may be stored in the remote memory storage device. Byway of example, and not limitation, FIG. 6 illustrates remoteapplication programs 648 as residing on memory device 645. It will beappreciated that the network connections shown are exemplary and othermeans of establishing a communications link between the computers may beused.

It should be understood that the various techniques described herein maybe implemented in connection with hardware or software or, whereappropriate, with a combination of both. Thus, the methods and apparatusof the presently disclosed subject matter, or certain aspects orportions thereof, may take the form of program code (i.e., instructions)embodied in tangible media, such as floppy diskettes, CD-ROMs, harddrives, or any other machine-readable storage medium wherein, when theprogram code is loaded into and executed by a machine, such as acomputer, the machine becomes an apparatus for practicing the presentlydisclosed subject matter. In the case of program code execution onprogrammable computers, the computing device generally includes aprocessor, a storage medium readable by the processor (includingvolatile and non-volatile memory and/or storage elements), at least oneinput device, and at least one output device. One or more programs thatmay implement or use the processes described in connection with thepresently disclosed subject matter, e.g., through the use of an API,reusable controls, or the like. Such programs are preferably implementedin a high-level procedural or object-oriented programming language tocommunicate with a computer system. However, the program(s) can beimplemented in assembly or machine language, if desired. In any case,the language may be a compiled or interpreted language, and combinedwith hardware implementations.

Although exemplary embodiments may refer to using aspects of thepresently disclosed subject matter in the context of one or morestand-alone computer systems, the said subject matter is not so limited,but rather may be implemented in connection with any computingenvironment, such as a network or distributed computing environment.Still further, aspects of the presently disclosed subject matter may beimplemented in or across a plurality of processing chips or devices, andstorage may similarly be affected across a plurality of devices. Suchdevices might include personal computers, network servers, handhelddevices, supercomputers, or computers integrated into other systems.

As is apparent from the above, all or portions of the various systems,methods, and aspects of the present embodiments may be embodied inhardware, software, or a combination of both. It is noted that theforegoing examples have been provided merely for the purpose ofexplanation and are in no way to be construed as limiting. While theembodiments have been described with reference to various embodiments,it is understood that the words which have been used herein are words ofdescription and illustration, rather than words of limitation. Further,although the embodiments been described herein with reference toparticular means, materials, the embodiments are not intended to belimited to the particulars disclosed herein; rather, the embodimentextends to all functionally equivalent structures, methods and uses,such as are within the scope of the appended claims.

What is claimed:
 1. A computer-readable storage medium comprising computer-readable instructions for recommending a location to a user and providing subjective information, the computer-readable instructions comprising instructions that: compile objective information associated with a location; compare the objective information to preferred criteria; compile subjective information associated with the location; compare the subjective information to the preferred criteria; and recommend the location to the user when the compiled objective information and the compiled subjective information at least in part correlates to the preferred criteria.
 2. The computer-readable storage medium of claim 1, wherein the instructions that recommend the location to the user comprise automatically generating a search report and providing the search report to the user.
 3. The computer-readable storage medium of claim 1, wherein at least a portion of the compiled subjective information is provided by a social network.
 4. The computer-readable storage medium of claim 1, wherein the preferred criteria is at least one of: objective location information or subjective location information.
 5. The computer-readable storage medium of claim 1, wherein the subjective information provided is associated with another person's profile, the other person's profile at least in part correlating to the user's profile.
 6. The computer-readable storage medium of claim 1, wherein instructions further comprise instructions that compare a user profile to a profile other than the user that is associated with a location to determine if there is a correlation between the user profile and the profile other than the user.
 7. A computer system for recommending a location to a user and providing subjective information, comprising: a memory configured to store instructions; a processor disposed in communication with said memory, wherein said processor upon execution of the instructions is configured to: compile objective information associated with a location; compare the objective information to preferred criteria; compile subjective information associated with the location; compare the subjective information to the preferred criteria; and recommend the location to the user when the compiled objective information and the compiled subjective information at least in part correlates to the preferred criteria.
 8. A computer system as recited in claim 7, wherein the instructions are further configured to compare a user profile to a profile other than the user that is associated with a location to determine if there is a correlation between the user profile and the profile other than the user. 